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\begin{document}

\mainmatter  % start of an individual contribution

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\title{Linked Personal Personal Information Management  for Mobile Users}

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\titlerunning{Linked Personal Personal Information Management}

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\author{Danh Le Phuoc
\and Anh Le Tuan\and Hanh Hoang Huu}
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\authorrunning{Danh Le Phuoc et al.}
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\institute{Digital Enterprise Research Institute ,\\
National University of Ireland Galway, Ireland \\
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\toctitle{Lecture Notes in Computer Science}
\tocauthor{Authors' Instructions}
\maketitle


\begin{abstract}
The abstract should summarize the contents of the paper and should
contain at least 70 and at most 150 words. It should be written using the
\emph{abstract} environment.
\keywords{mobile, personal information system}
\end{abstract}


\section{Introduction}
[Intro here]

\subsection{Motivated Use cases}

 Mobile devices can store a lot of personal infromation such as contact list, message, email,   social network account, photo, video.
The idea is from the Semantic Desktop. With the apprance of RDF store in mobile, that we are able to link mobile applications together and intergrate with the social network.

People tend to use thier mobile device more often than the desktop. 

People tend to use the mobile device to connect to the social network. 
 
Able to tag people to a meeting, a photo, a video.

 - Contact list management. 
    + Contact list can be synchronize from social network
    + Contact list can be convert from local phone contact
Able to detect the contact node in the social network.



 The problem is how to match them together. This can be solve the issue how to detect the relationship between phone owner and his friend.

Related material required.
 
 - Calenda management
 Not decide yet:
  + birthay annotation, meeting annotation.

 - Media annotation. 
  + The use case idea can take from the RDF content provider. Build an interface which is able for user to annotate or tag to image.




\section{Related work}

\section{Data integration and alignment}

[Danh to write this section]

Person-centralized data, data is not only about one personal but about all the social relationship that a person have.

- What kind of data to be taken in paper's consideration

	+ Give examples from data from Semantic Life, Social network application~\cite{Tramp:2010}, Semantic desktops

Data circle : User and his community created data in data silos how can these information can be linked and shared? 
In order to link these information there must be place holders that can tight thing to gather, in this case, person is a centric information,
there fore person identification will be the first class citizen in the personal graphs of data/ personal view of the data/ personal data space. 

As the data comes from different data silos, for example Facebook, twitter, google email, linked in, foaf file, etc, there are different ways to identify 
a personal because there would be several ID(URI, blank node) to identification a person). This fact leads to the  
ID consolidation requirements  Idmesh~\cite{Cudre-Mauroux:2009}, sameAs, ...

- Explain how the ID consolidation can be handled here : Master ID schema


As personal information are accessible as several fragments as graphs with different identification schema. On top of that, the linkages among 
URI/blank nodes are published or transformed in different vocabulary. In order to align these linked information in a same graph to give user a single
view about their personal data space, we need a mechanism for aligning/patching graphs. 

-Explain how to align distributed data into single graph with : mapping rules, multi-layers graph.
 
"ANH: I suggest the the mapping rule is a list of triples (A sameAs B) to connect 2 Node. We've decided how to use the SameAs reasoning to match them together."


\section{Context-based information navigation}

[Mr Hanh to outline and  this section]
 
-Context-based information filtering and suggestion

-Context-based query on top of SPARQL and indexing system of mobile triple storage....

\section{System design and implementation}

-Architecture : Wrappers(Facebook, twitter, Phone, linked in, etc) , data storage(phone triple storage), 
ID-reasoner ( SameAs reasoner).
   
 Linkedin wrapper is done. 
 Facebook wrapper is done. 
Later we need decide to get triple directly from the facebook graph api or use the wrapper.


-System design

-Implementation details
	
	+triple storage for mobile ~\cite{Furstenau:2009}
	
	+ Wrapper
  
	+Query interfaces 

\section{Demo and evaluation}

-Describe demo and screen shot

-Some evaluations: Evaluation metrics : query response time vs size of data.

\section{Conclusion and future work}

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